1. Field of the Invention
The present invention relates to a hybrid beamforming apparatus and a method for the same, more particularly to a hybrid beamforming apparatus for enhancing immunity for multipath effect with lower system complexity and a method for the same.
2. Description of Prior Art
In wireless communication system, the multipath effect and fading effect are two major reasons accounting for interference. Especially in metropolitan area, the received signal is subjected to multiple reflections by buildings between mobile stations and base stations. The channel characteristics have dynamical change with the movement of mobile station. To overcome multipath effect, an equalizer can be used to provide compensation. However, the complexity of the equalizer is increased with channel delay. Multicarrier techniques such as OFDM are adopted to reduce equalizer complexity and applied to IEEE802.11a, IEEE802.11g, and IEEE802.16a based systems.
Moreover, multiple-antenna system, such as smart antenna system, is developed to overcome fading effect and co-channel interference. The received signals from antennas of the multiple-antenna system are added to form a beam and the interference can be removed. The performance of the multiple-antenna system could be enhanced by diversity combining techniques such as Maximum Ratio Combining, Equal Gain Combining, Selective Combining, or adaptive algorithm.
In multiple-antenna system, a plurality of antennas is used to form a spatial filter. The signals propagated from a specific direction will form a beam with maximal gain and signals from other directions are rejected to eliminate interference. Therefore, the multiple-antenna system is also referred as smart antenna system or adaptive antenna array system.
FIG. 1 shows a block diagram of a prior art beamforming apparatus 10 for wireless communication system. The signals yi(n) received by the antennas 100 are multiplied by corresponding weight coefficient wi*, and then processed by an added 104. The sum z(n) thereof is output with following expression:
      z    ⁡          (      n      )        =            ∑              i        =        1            M        ⁢                  ⁢                  w        i        *            ⁢                        y          i                ⁡                  (          n          )                    
wherein n indicates different time and weight coefficients wi* are selected to achieve maximal gain and deduced by adaptive algorithm. The adaptive algorithm can be, but not limited to ML (Maximum Likelihood), MSNR (Maximum Signal to Noise Ratio), MSINR (Maximum Signal to Interference Noise Ratio), and MMSE (Minimum Mean Square Error) etc.
The deduction of weight coefficients is exemplified by MMSE criterion below. At first a cost function J is defined as following:J=E[|d(n)−z(n)|2]                wherein d(n) is training signal from the sender, and the weight coefficients deduced by MMSE algorithm are represented by Wiener-Hopf equation.wopt=Ryy−1ryd where        
            w      opt        =                  [                              w            1                    ,                      w            2                    ,          ⋯          ⁢                                          ,                      w            M                          ]            T        ,            r              y        ⁢                                  ⁢        d              =                  [                              r                                          y                1                            ⁢              d                                ,                      r                                          y                2                            ⁢              d                                ,          ⋯          ⁢                                          ,                      r                                          y                M                            ⁢              d                                      ]            T        ,            R      yy        =                  [                                                            r                                                      y                    1                                    ⁢                                      y                    1                                                                                                      r                                                      y                    1                                    ⁢                                      y                    2                                                                                      ⋯                                                      r                                                      y                    1                                    ⁢                                      y                    M                                                                                                                          r                                                      y                    2                                    ⁢                                      y                    1                                                                                      ⋯                                                                                                                                                                                                  ⋮                                                                                                          ⋯                                      ⋮                                                                          r                                                      y                    M                                    ⁢                                      y                    1                                                                                      ⋯                                      ⋯                                                      r                                                      y                    M                                    ⁢                                      y                    M                                                                                      ]            .      andryid=E[yi(n)d* n)] is the cross-correlation coefficient of yi(n) and d(n), ryiyj=E[yi(n)yj*(n)] is cross-correlation coefficient of yi(n) and yj(n) when i≠j or auto-correlation coefficient of yi(n) and yj(n) when i=j.
The calculation of Ryy and ryd can be performed in time domain and frequency domain, which will be stated in more detail below.
FIG. 2A shows a block diagram of a prior art time-domain beamforming apparatus 20, which comprises a plurality of antennas 200, a weight-coefficient generator 202 for receiving the detected signals yi(n) of the antennas 200 and a training signal d(n), an adder 204 and an FFT (Fast Fourier Transform) 206. As can be seen in this figure, the prior art time-domain beamforming apparatus 20 calculates only one inverse matrix Ryy and no other FFT operation. The calculation of Ryy and ryd are performed by time domain sampling to reduce complexity. More particularly, yi(n) are obtained by directly sampling the detected signal of antennas and d(n) is time-domain training signal. The performance of above time-domain beamforming apparatus 20 is sensitive to channel characteristic. The BER (bit error rate) of the time-domain beamforming apparatus 20 is rapidly increased as the delay profile related to multipath effect is increased. FIG. 2B shows the performance of the prior art time-domain beamforming apparatus. As shown in this figure, the BER of the system is excessive when the delay time exceeds 50 ns.
FIG. 3A shows a block diagram of a prior art frequency-domain beamforming apparatus 30, which comprises a plurality of antennas 300, a plurality of FFTs 306 for converting time-domain received signals to frequency-domain counterparts, a plurality of weight-coefficient generators 302 for receiving the frequency-domain signals of the FFTs 306, a plurality of adders 304 for summing the product of weigh coefficient and frequency-domain signals to obtain frequency-domain data signal for each subcarrier. In the prior art frequency-domain beamforming apparatus 30, the calculation of RYY(k) and rYD(k) are performed in frequency domain. The signals received by antennas are converted by N-point FFT and the output Y(k) is generated for each subcarrier, wherein capital symbol in sub Y and D indicate frequency-domain signals and the k is number of subcarrier. Therefore, RYY(k) and rYD(k) could be calculated for each subcarrier.
More particularly,
      Z    ⁡          (      k      )        =            ∑              i        =        1            M        ⁢                  ⁢                            w          i          *                ⁡                  (          k          )                    ⁢                        Y          i                ⁡                  (          k          )                    is the output of the frequency-domain beamforming apparatus 30, wopt(k)=RYY−1(k)rYD(k) is the optimal weight coefficients deduced by Wiener-Hopf equation, and
                    w        opt            ⁡              (        k        )              =                  [                                            w              1                        ⁡                          (              k              )                                ,                                    w              2                        ⁡                          (              k              )                                ,          ⋯          ⁢                                          ,                                    w              M                        ⁡                          (              k              )                                      ]            T        ,                    r        YD            ⁡              (        k        )              =                  [                              r                                                            Y                  1                                ⁡                                  (                  k                  )                                            ⁢                              D                ⁡                                  (                  k                  )                                                              ,                      r                                                            Y                  2                                ⁡                                  (                  k                  )                                            ⁢                              D                ⁡                                  (                  k                  )                                                              ,          ⋯          ⁢                                          ,                      r                                                            Y                  M                                ⁡                                  (                  k                  )                                            ⁢                              D                ⁡                                  (                  k                  )                                                                    ]            T        ,                    R        YY            ⁡              (        k        )              =                  [                                                            r                                                                            Y                      1                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      1                                        ⁡                                          (                      k                      )                                                                                                                          r                                                                            Y                      1                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      2                                        ⁡                                          (                      k                      )                                                                                                          ⋯                                                      r                                                                            Y                      1                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      M                                        ⁡                                          (                      k                      )                                                                                                                                              r                                                                            Y                      2                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      1                                        ⁡                                          (                      k                      )                                                                                                          ⋯                                                                                                                                                                                                  ⋮                                                                                                          ⋯                                      ⋮                                                                          r                                                                            Y                      M                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      1                                        ⁡                                          (                      k                      )                                                                                                          ⋯                                      ⋯                                                      r                                                                            Y                      M                                        ⁡                                          (                      k                      )                                                        ⁢                                                            Y                      M                                        ⁡                                          (                      k                      )                                                                                                          ]            .      
As can be seen in FIG. 3A, the frequency-domain beamforming apparatus 30 has significant increase in system complexity as being compared with time-domain beamforming apparatus. The inverse matrix calculation is proportional to subcarrier number and the FFT calculation is proportional to antenna number. More particularly, the system complexity of frequency-domain beamforming apparatus is (subcarrier number×antenna number) times complicated than the time-domain beamforming apparatus.
FIG. 3B shows the performance of the prior art frequency-domain beamforming apparatus. As shown in this figure, the performance of the frequency-domain beamforming apparatus is not deteriorated by channel delay. The BER keeps nearly constant as the channel delay is increased. The frequency-domain beamforming apparatus achieves immunity to multipath effect at the expense of increased system complexity.
In an OFDM (Orthogonal Frequency Division Multiplexing) system, each subcarrier transmits through one-path channel and the multipath effect can be reduced. It is benefic to exploit the property of OFDM system and use it with frequency-domain beamforming apparatus to obtain immunity to multipath effect with less system complexity.